AN EMPIRICAL STUDY OF THE PROBABILITY DENSITY FUNCTION OF HF NOISE (PART II)

2008 ◽  
Vol 08 (03n04) ◽  
pp. L305-L314 ◽  
Author(s):  
J. GIESBRECHT
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
South Australia ◽  
Noise Model ◽  
Modulation Recognition ◽  
Noise Sources ◽  
Noise Density ◽  
Automatic Modulation Recognition ◽  
Definition Of

The impetus for investigating the probability density function of high-frequency (HF) noise arises from the requirement for a better noise model for automatic modulation recognition techniques. Many current modulation recognition methods still assume Gaussian noise models for the transmission medium. For HF communications this can be an incorrect assumption. Whereas a previous investigation [1] focuses on the noise density function in an urban area of Adelaide Australia, this work studies the noise density function in a remote country location east of Adelaide near Swan Reach, South Australia. Here, the definition of HF noise is primarily of natural origins – it is therefore impulsive – and excludes man-made noise sources. A new method for measuring HF noise is introduced that is used over a 153 kHz bandwidth at various frequencies across the HF band. The method excises man-made signals and calculates the noise PDF from the residue. Indeed, the suitability of the Bi-Kappa distribution at modeling HF noise is found to be even more compelling than suggested by the results of the earlier investigation.

scholarly journals Maximum-likelihood estimation of the parameters of a four-parameter class of probability distributions

1988 ◽  
Vol 31 (2) ◽  
pp. 271-283 ◽  
Author(s):  
Siegfried H. Lehnigk
Keyword(s):  
Maximum Likelihood ◽  
Probability Density Function ◽  
Maximum Likelihood Estimation ◽  
Probability Density ◽  
Density Function ◽  
Probability Distributions ◽  
Likelihood Estimation ◽  
Initial Shape ◽  
Definition Of ◽  
Image Position

We shall concern ourselves with the class of continuous, four-parameter, one-sided probability distributions which can be characterized by the probability density function (pdf) classIt depends on the four parameters: shift c ∈ R, scale b > 0, initial shape p < 1, and terminal shape β > 0. For p ≦ 0, the definition of f(x) can be completed by setting f(c) = β/bΓ(β−1)>0 if p = 0, and f(c) = 0 if p < 0. For 0 < p < 1, f(x) remains undefined at x = c; f(x)↑ + ∞ as x↓c.

scholarly journals Exploring Finite-Sized Scale Invariance in Stochastic Variability with Toy Models: The Ornstein–Uhlenbeck Model

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1927
Author(s):  
Nachiketa Chakraborty
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Scale Invariance ◽  
Finite Size ◽  
Fundamental Property ◽  
Cosmic Ray ◽  
Self Similarity ◽  
Definition Of ◽  
Stochastic Properties

Stochastic variability is ubiquitous among astrophysical sources. Quantifying stochastic properties of observed time-series or lightcurves, can provide insights into the underlying physical mechanisms driving variability, especially those of the particles that radiate the observed emission. Toy models mimicking cosmic ray transport are particularly useful in providing a means of linking the statistical analyses of observed lightcurves to the physical properties and parameters. Here, we explore a very commonly observed feature; finite sized self-similarity or scale invariance which is a fundamental property of complex, dynamical systems. This is important to the general theme of physics and symmetry. We investigate it through the probability density function of time-varying fluxes arising from a Ornstein–Uhlenbeck Model, as this model provides an excellent description of several time-domain observations of sources like active galactic nuclei. The probability density function approach stems directly from the mathematical definition of self-similarity and is nonparametric. We show that the OU model provides an intuitive description of scale-limited self-similarity and stationary Gaussian distribution while potentially showing a way to link to the underlying cosmic ray transport. This finite size of the scale invariance depends upon the decay time in the OU model.

The cost of a carrier-borne epidemic

1974 ◽  
Vol 11 (4) ◽  
pp. 642-651 ◽  
Author(s):  
D. Jerwood
Keyword(s):  
Probability Density Function ◽  
Probability Distribution ◽  
Probability Density ◽  
Density Function ◽  
Expected Number ◽  
Stochastic Epidemic ◽  
Definition Of ◽  
The Cost ◽  
General Stochastic

In this paper, the cost of the carrier-borne epidemic is considered. The definition of duration, as used by Weiss (1965) and subsequent authors, is generalised and the probability distribution for the number of located carriers is obtained. One component of cost, namely the area generated by the trajectory of carriers, is examined and its probability density function derived. The expected area generated is then shown to be proportional to the expected number of carriers located during the epidemic, a result which has an analogue in the general stochastic epidemic.

AN EMPIRICAL STUDY OF THE PROBABILITY DENSITY FUNCTION OF HF NOISE

2006 ◽  
Vol 06 (02) ◽  
pp. L117-L125 ◽  
Author(s):  
J. GIESBRECHT ◽  
R. CLARKE ◽  
D. ABBOTT
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Gaussian Noise ◽  
Satellite Communications ◽  
Time Of Day ◽  
Modulation Recognition ◽  
Long Distance ◽  
Radio Communications ◽  
Probability Density Function Pdf

To many, high-frequency (HF) radio communications is obsolete in this age of long-distance satellite communications and undersea optical fiber. Yet despite this, the HF band is used by defense agencies for backup communications and spectrum surveillance, and is monitored by spectrum management organizations to enforce licensing. Such activity usually requires systems capable of locating distant transmitters, separating valid signals from interference and noise, and recognizing signal modulation. Our research targets the latter issue. The ultimate aim is to develop robust algorithms for automatic modulation recognition of real HF signals. By real, we mean signals propagating by multiple ionospheric modes with co-channel signals and non-Gaussian noise. However, many researchers adopt Gaussian noise for their modulation recognition algorithms for the sake of convenience at the cost of accuracy. Furthermore, literature describing the probability density function (PDF) of HF noise does not abound. So we describe a simple empirical technique, not found in the literature, that supports our work by showing that the probability density function (PDF) for HF noise is generally not Gaussian. In fact, the probability density function varies with the time of day, electro-magnetic environment, and state of the ionosphere.

The cost of a carrier-borne epidemic

1974 ◽  
Vol 11 (04) ◽  
pp. 642-651 ◽  
Author(s):  
D. Jerwood
Keyword(s):  
Probability Density Function ◽  
Probability Distribution ◽  
Probability Density ◽  
Density Function ◽  
Expected Number ◽  
Stochastic Epidemic ◽  
Definition Of ◽  
The Cost ◽  
General Stochastic

In this paper, the cost of the carrier-borne epidemic is considered. The definition of duration, as used by Weiss (1965) and subsequent authors, is generalised and the probability distribution for the number of located carriers is obtained. One component of cost, namely the area generated by the trajectory of carriers, is examined and its probability density function derived. The expected area generated is then shown to be proportional to the expected number of carriers located during the epidemic, a result which has an analogue in the general stochastic epidemic.

scholarly journals The Long Term Behaviour of Classical Old Novae

1990 ◽  
Vol 122 ◽  
pp. 13-23
Author(s):  
A. Bianchini
Keyword(s):  
Mass Transfer ◽  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Time Scales ◽  
Transfer Rate ◽  
Mass Transfer Rate ◽  
Solar Type ◽  
Definition Of

AbstractQuiescent novae are more stable against mass transfer rate than dwarf novae. They may however show cyclical variations of their quiescent magnitudes on time scales of years, probably caused by solar–type cycles of activity of the secondary. The probability density function of the periods of the cycles observed in CVs is similar to that for single stars. Sometimes, periodic or quasi periodic light variations on time scales of tens to hundreds of days are also observed. Although the magnitudes of prenovae and postnovae are essentially the same, the definition of the magnitude of a quiescent nova is still uncertain. At present, the hibernation theory for old novae seems to be supported only by the observations of two very old novae.

Sign in / Sign up

Export Citation Format

Share Document